Academic engagement and emotional well-being of secondary students during the COVID-19 pandemic
Bibliographic record
Abstract
This study investigates how students experienced school during the COVID-19 pandemic to understand the role of schooling in social reproduction during this time of school closures. Using a mixed methods design, I conducted a secondary analysis of a Toronto District School Board-administered survey of high school students, as well as new interviews and focus groups with Grade 11 students, and interviews with high school teachers. I analyzed the differences in students’ academic engagement and emotional well-being by student race, gender, program type (regular- vs. high-stream), and school socio-economic status. The findings suggest that students in high-stream programs with a stronger sense of community were better able to customize their level of engagement with school than students in regular-stream programs.Surprisingly, White students and students from high-SES schools reported less emotional well-being than racialized students and those from low-SES schools. I posit that, during the pandemic, when school was mostly or completely online, (a) classes were less likely to provide students with a sense of community (unless it was established before the pandemic), and (b) learning tasks were less likely to challenge students’ higher-order thinking skills, as compared to in-person learning. However, the difference between in-person and pandemic-era schooling may have been more pronounced for students attending high-stream programs than those from less privileged backgrounds and attending regular-stream programs. This analysis draws on Bourdieu’s concept of cultural capital, Lareau’s theories with respect to the role of parenting styles in social reproduction, and Oakes’ theories linking high school streaming practices and learning environment quality. Sociologists have theorized that elements of cultural capital and a “sense of entitlement” help White middle-class students excel at school. This study expands on these theories by emphasizing the role that school plays in social reproduction. I suggest that students’ sense of entitlement (or constraint) in schools are partly shaped by their experiences with high- vs. regular-stream programs. This framing highlights the importance of equitable access to high-quality learning opportunities and a sense of community in schools, as these elements can contribute to students’ cultural capital beyond what is developed in the home.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".